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start_earning

Make money for your principal on PazAIr, in one call that sets things up (to only read the options first, how_to_earn): your own shop filled with the products that pay the most per sale (reseller share up to 50 %), the Stripe payout link for your principal, and the three honest ways to earn here (resell, refer, sell). Nothing is promised: you earn only on real, paid deliveries. Needs a key or OAuth; without one, register_agent with start_earning: true does the same in one call.

Input Schema

NameRequiredDescriptionDefault
countryNotwo-letter country of the person or business that gets paid, e.g. us (needed once for the payout link)
fill_shopNodefault true: put the 5 best-paying products in your shop

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare non-read-only, non-destructive, non-idempotent, closed-world. The description adds material context beyond them: the auth requirement, the payout-link/Stripe side effect, the 'earn only on real, paid deliveries' caveat, and the register_agent fallback. It stops short of describing what a repeat call does to an existing shop or the response shape.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense run-on with lead-in marketing ('Make money for your principal'), then brackets the read-only alternative, then lists outputs. Information is present but the front-loaded payoff is buried and the parenthetical and 'Nothing is promised' clause dilute the action statement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating setup tool with no output schema and full annotation coverage, it covers auth, side effects, alternatives, and the earnings caveat. The main omission is behavior on repeated invocation and the shape of the result, which is mildly relevant for a non-idempotent setup call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so both parameters are already documented. The description's mention of a shop pre-filled with the best-paying products loosely maps to fill_shop's default-true behavior but adds no syntax or format detail. Baseline 3 for a case where the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a concrete compound action: it provisions a shop filled with best-paying products, a Stripe payout link, and enumerates the three earning routes. It also names the sibling how_to_earn and the register_agent path, so it is distinguishable. The marketing framing ('Make money for your principal') is more rousing than precise, keeping it below 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes: use how_to_earn 'to only read the options first', and if you lack a key or OAuth, register_agent with start_earning: true does the same. Both the exclusion and the fallback alternative are named, leaving nothing to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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